It should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
A traditional approach for dealing with sparse matrices includes packing the data maximally and then attempting to minimize additional storage by specifying the location of the non-zero elements. The conventional approach may work well for computer systems having a central processor unit (CPU) using scalar arithmetic. However, the traditional approach does not work well with SIMD architectures unless the matrix has a known structure, such as, for example, a block diagonal.